Dissertations / Theses on the topic 'Indoor positioning systems (Wireless localization)'

Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2015.
Recently, the deployment and availability of wireless technology have led to the development of location and positioning services. These Location Based Services (LBSs) are attracting the attention of researchers and mobile service providers. With the importance of ubiquitous computing, the main challenge seen in the LBS is in the mobile positioning or localization within reasonable and certain accuracy. The Global Positioning System (GPS), as a widely known and used navigation system, is only appropriate for use in outdoor environments, due to the lack of line-of-sight (LOS) in satellite signals that they cannot be used accurately inside buildings and premises. Apart from GPS, Wi-Fi is among others, a widely used technology as it is an already existing infrastructure in most places. This work proposes and presents an indoor positioning system. As opposed to an Ad-hoc Positioning System (APS), it uses a Wireless Mesh Network (WMN). The system makes use of an already existing Wi-Fi infrastructure. Moreover, the approach tests the positioning of a node with its neighbours in a mesh network using multi-hopping functionality. The positioning measurements used were the ICMP echo requests, RSSI and RTS/CTS requests and responses. The positioning method used was the trilateral technique, in combination with the idea of the fingerprinting method. Through research and experimentation, this study developed a system which shows potential as a positioning system with an error of about 2 m – 3 m. The hybridization of the methods proves an enhancement in the system though improvements are still required

A technique is proposed to improve the accuracy of indoor positioning systems based on WIFI radio-frequency signals by using dynamic access points and fingerprints (DAFs). Moreover, an indoor position system that relies solely in DAFs is proposed. The walking pattern of indoor users is classified as dynamic or static for indoor positioning purposes. I demonstrate that the performance of a conventional indoor positioning system that uses static fingerprints can be enhanced by considering dynamic fingerprints and access points. The accuracy of the system is evaluated using four positioning algorithms and two random access point selection strategies. The system facilitates the location of people where there is no wireless local area network (WLAN) infrastructure deployed or where the WLAN infrastructure has been drastically affected, for example by natural disasters. The system can be used for search and rescue operations and for expanding the coverage of an indoor positioning system.

Large enterprises are often interested in tracking objects and people within buildings to improve resource allocation and occupant experience. Infrastructure-based indoor positioning systems (IIPS) can provide this service at low-cost by leveraging already deployed Wi-Fi infrastructure. Typically, IIPS perform localization and tracking of devices by measuring only Wi-Fi signals at wireless access points and do not rely on inertial sensor data at mobile devices (e.g., smartphones), which would require explicit user consent and sensing capabilities of the devices. Despite these advantages, building an economically viable cost-effective IIPS that can accurately and simultaneously track many devices over very large buildings is difficult due to three main challenges. First, Wi-Fi signal measurements are extremely noisy due to unpredictable multipath propagation and signal attenuation. Second, as the IIPS obtain measurements in a best effort manner without requiring any applications installed on a tracked device, the measurements are temporally sparse and non-periodic, which makes it difficult to exploit historical measurements. Third, the cost-effective IIPS have limited computational resources, in turn limiting scalability in terms of the number of simultaneously tracked devices. Prior approaches have narrowly focused on either improving the accuracy or reducing the complexity of localization algorithms. To compute the location at the current time step, they typically use only the latest explicit Wi-Fi measurements (e.g., signal strengths). The novelty of our approach lies in considering contexts of a device that can provide useful indications of the device's location. One such example of context is device motion. It indicates whether or not the device's location has changed. For a stationary device, the IIPS can either skip expensive device localization or aggregate noisy, temporally sparse location estimates to improve localization accuracy. Another example of context applicable to a moving device is a floor map that consists of pre-defined path segments that a user can take. The map can be leveraged to constrain noisy, temporally sparse location estimates on the paths. The thesis of this dissertation is that embedding context-aware capabilities in the IIPS enhances its performance in tracking many devices simultaneously and accurately. Specifically, we develop motion detection and map matching to show the benefits of leveraging two critical contexts: device motion and floor map. Providing motion detection and map matching is non-trivial in the IIPS where we must rely only on data from the Wi-Fi infrastructure. This thesis makes two contributions. First, we develop feature-based and deep learning-based motion detection models that exploit temporal patterns in Wi-Fi measurements across different access points to classify device motion in real time. Our extensive evaluations on datasets from real Wi-Fi deployments show that our motion detection models can detect device motion accurately. This, in turn, allows the IIPS to skip repeated location computation for stationary devices or improve the accuracy of localizing these devices. Second, we develop graph-based and image-based map matching models to exploit floor maps. The novelty of the graph-based approach lies in applying geometric and topological constraints to select which path segment to align the current location estimate. Our graph-based map matching can align a location estimate of a user device on the path taken by the user and close to the user's current location. The novelty of the image-based approach lies in representing for the first time, input data including location estimates and the floor map as 2D images. This novel representation enables the design, development, and application of encoder-decoder neural networks to exploit spatial relationships in input images to potentially improve location accuracy. In our evaluation, we show that the image-based approach can improve location accuracy with large simulated datasets, compared to the graph-based approach. Together, these contributions enable improvement of the IIPS in its ability to accurately and simultaneously track many devices over large buildings.

Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2015.
Navigation systems are known to provide time and location information for easy and accurate navigation in a specified environment. While Global Positioning System (GPS) has recorded a considerable success for navigating outdoors, the absence of GPS indoors has made orientation in an indoor environment challenging. Furthermore, existing technologies and methods of indoor positioning and navigation, such as WLAN, Bluetooth and Infrared, have been complex, inaccurate, expensive and challenging to implement; thereby limiting the usability of these technologies in less developed countries. This limitation of navigation services makes it difficult and time consuming to locate a destination in indoor and closed spaces. Hence, recent works with Near Field Communication (NFC) has kindled interest in positioning and navigation. While navigating, users in less developed nations face several challenges, such as infrastructure complexity, high-cost solution, inaccuracy and usability. However, this research focuses on providing interventions to alleviate usability challenges, in order to strengthen the overall accuracy and the navigation effectiveness in stringent environments through the experiential manipulation of technical attributes of the positioning and navigation system in indoor environments. Therefore, this study adopted the realist ontology and the positivist epistemological approach. It followed a quantitative and experimental method of empirical enquiry, and software engineering and synthesis research methods. The study entails three implementation processes, namely map generation, positioning framework and navigation service using a prototype mobile navigation application that uses the NFC technology. It used open-source software and hardware engineering tools, instruments and technologies, such as Ubuntu Linux, Android Software Development Kit, Arduino, NFC APIs and PandaBoard. The data was collected and the findings evaluated in three stages: pre-test, experiment and post-test.

Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2017.
The implosion of the mobile phones, mobile applications and social media in recent years has triggered a great interest for more dedicated user-generated contents. Mobile users being the focal point, these modern virtual platforms depend on and live for collecting, structuring and manipulating the very fine-grained details about users' day-to-day activities. Since every human activity takes place in a geographical context, location information ranks high among the set of data to gather about user's daily life. User's specific location details can help filter content to serve and retrieve from them. Therefore, location-based services have been developed and successfully integrated into most virtual platforms in the quest for these precious data. However, location-based services do not fulfil all requirements. They depend on a range of positioning systems which show numerous limitations. None of the existing positioning systems is perfectly accurate. Today, it is therefore difficult to pinpoint a user in a venue using location-based services. Nevertheless, with the set of existing technology and techniques, it is possible to estimate and track users’ whereabouts in real-time. Providing the best possible estimation of user's position within a given venue can help achieve better user engagement. Depending on the gap of accuracy, the end result may actually match the outcome expected from perfectly accurate positioning systems. In this work, the focus is to develop a prototype positioning system which provides the best estimation of user's position in real-time in relation to a targeted venue or location. Through a series of research and comparison study, the most suited technology and techniques are objectively selected to build the intended prototype. The challenge of indoor positioning is also addressed in this work – bearing in mind the fact that this prototype is set to work accurately and efficiently in any geographical location and structure. The prototype is evaluated according to a set of predefined standard metrics, and theories are extracted to grow knowledge about this trending topic.

Mestrado em Engenharia Electrónica e de Telecomunicações
The increasing demand for tracking solutions in indoor environments has led to the development of many indoor location systems based in the most diverse technologies. They are trying to fill a market niche left by the current available location systems such as the well-known Global Positioning System (GPS). These systems are limited to an outdoor usage due to the drastic attenuation of the GPS signals in closed areas and they cannot provide enough resolution to meet the requirements of certain applications. Therefore, it’s here proposed the conception of a system capable of locating a mobile module in indoor environments with an accuracy of a few centimeters. The system’s concept is based in measuring the time difference of arrival (TDOA) between a radio frequency signal and an ultrasonic burst in order to measure distances. The huge difference between the propagation velocities of RF waves comparatively to sound waves allows the system to accurately measure the time difference between the two arrivals and use that value to estimate the distance that separates the source from the destination. This document describes the development of all the necessary hardware for the conception of a final prototype and all the aspects regarding the software implementation. This system is composed by two types of devices that can be divided in Ultrasonic (US) transmitters and receivers. Each device is equipped with a RF module that allows them to communicate through a wireless network based in the IEEE802.15.4 protocol. In the end, a functional prototype was achieved that was subsequently submitted to several tests in order to evaluate its performance. These tests corroborated the viability of this localization method with the prototype achieving a remarkable precision level.
A crescente demanda por soluções de rastreamento em ambientes interiores levou ao desenvolvimento de vários sistemas de localização baseados nas mais diversas tecnologias. Eles vêm tentar colmatar um nicho de mercado deixado pelos sistemas de localização actualmente disponíveis como o caso do bem conhecido Sistema de Posicionamento Global (GPS). Estes sistemas estão limitados ao uso exterior devido à drástica atenuação dos sinais GPS em áreas fechadas e eles não oferecem resolução suficiente para cumprir os requisitos de certas aplicações. Por conseguinte, é aqui proposta a concepção de um sistema capaz de localizar um módulo móvel em ambientes interiores com uma resolução de alguns centímetros. O conceito do sistema é baseado na medição da diferença dos tempos de chegada entre um sinal de radiofrequência e um sinal de ultra-sons de forma a calcular distâncias. A enorme diferença entre as velocidades de propagação das ondas RF comparativamente às ondas sonoras permitem ao sistema medir com precisão a diferença entre o tempo de chegada dos dois sinais e usar esse valor para estimar a distância que separa a fonte do destino. Este documento descreve o desenvolvimento de todo o hardware necessário para a concepção de um protótipo bem como todos os aspectos relativos à implementação de software. Este sistema é composto por dois tipos de dispositivos que podem ser divididos em transmissores e receptores de sinais ultrassónicos. Cada dispositivo está equipado com um módulo de radiofrequência que lhes permite comunicar através de uma rede sem fios baseada no protocolo IEEE802.15.4. No final, foi alcançado um protótipo funcional que posteriormente foi submetido a vários testes de forma a avaliar o seu desempenho. Estes testes vieram corroborar a viabilidade deste método de localização com o protótipo a atingir um notável nível de precisão.

Alternate realities have fascinated mankind since early prehistory and with the advent of the computer and the smartphone we have seen the rise of many different categories of alternate reality that seek to augment, diminish, mix with or ultimately replace our familiar real world in order to expand our capabilities and our understanding. This thesis presents parallel reality as a new category of alternate reality which further addresses the vacancy problem that manifests in many previous alternate reality experiences. Parallel reality describes systems comprising two environments that the user may freely switch between, one real and the other virtual, both complete unto themselves. Parallel reality is framed within the larger ecosystem of previously explored alternate realities through a thorough review of existing categorisation techniques and taxonomies, leading to the introduction of the combined Milgram/Waterworth model and an extended definition of the vacancy problem for better visualising experience in alternate reality systems. Investigation into whether an existing state of the art alternate reality modality (Situated Simulations) could allow for parallel reality investigation via the Virtual Time Windows project was followed by the development of a bespoke parallel reality platform called Mirrorshades, which combined the modern virtual reality hardware of the Oculus Rift with the novel indoor positioning system of IndoorAtlas. Users were thereby granted the ability to walk through their real environment and to at any point switch their view to the equivalent vantage point within an immersive virtual environment. The benefits that such a system provides by granting users the ability to mitigate the effects of the extended vacancy problem and explore parallel real and virtual environments in tandem was experimentally shown through application to a use case within the realm of cultural heritage at a 15th century chapel. Evaluation of these user studies lead to the establishment of a number of best practice recommendations for future parallel reality endeavours.

Mestrado em Engenharia Electrónica e Telecomunicações
The rapid evolution of Wireless technologies, speci cally in the area of Wireless Sensor Networks (WSN), has led to a growing demand for the availability of information anywhere, about anything. WSN are being widely used, for example, in domotic applications, partly due to their relatively low cost and their low energy consumption nature. These characteristics make this kind of networks very useful to ll some gaps in other applications, e.g. localization-related applications. This dissertation focuses, then, on the growing importance and demand for localization of people or objects and presents one of the possible approaches to the problem of indoor localization. By merging two di erent wireless technologies (IEEE 802.11 and IEEE 802.15.4), it is possible to make wireless communications more e cient for some applications. The merge is achieved by the creation of a Gateway, with support for both standards and near-transparent translation between them. This allows cheaper 802.15.4 devices to communicate with regular 802.11 TCP/IP (Transmission Control Protocol/Internet Protocol) based networks, giving space for inumerous applications, speci cally for localization purposes, which is the main goal of this project. The creation of the necessary hardware infrastructures and its respective control software, even though the solution may be used in a large range of applications, is more speci cally directed to comply with some of the requirements of the localization system to be created, eventually. So, in addition to the Gateways that make the translation between the two already referred standards, this project consists in the creation of Tags, small low-power and low-cost end-devices that are to be attached to the objects in need of localization features. These devices communicate with the Gateways by means of an 802.15.4 connection and indirectly advertise their location, by providing the signal strength of the connection. This data is computed and can be accessed in any personal computer with a web browser and a connection to the network.
A r apida evolu c~ao das tecnologias de redes sem os, em particular na area das Wireless Sensor Networks (WSN), levou ao crescimento da necessidade de obter informa c~oes, sobre qualquer coisa, em qualquer lugar. As WSN t^em sido amplamente utilizadas, por exemplo, em aplica c~oes da area da dom otica, em parte devido ao seu relativamente baixo custo e baixo consumo de energia. Estas caracter sticas fazem com que este tipo de redes seja bastante importante no preenchimento de algumas lacunas ainda existentes noutras aplica c~oes, como por exemplo, aplica c~oes de localiza c~ao de objectos. Esta disserta c~ao foca-se, ent~ao, na crescente import^ancia e necessidade de localiza c~ao de pessoas e objectos e apresenta uma das poss veis abordagens ao problema de localiza c~ao em espa cos fechados. Atrav es da integra c~ao m utua de duas tecnologias wireless diferentes (IEEE 802.11 e 802.15.4) e poss vel tornar as comunica c~oes wireless bastante mais e cientes em alguns campos de aplica c~ao. Esta integra c~ao e conseguida com a cria c~ao de um Gateway com suporte para ambos os standards referidos e tradu c~ao quase transparente (para o utilizador) entre ambos. Assim, passa a ser poss vel a comunica c~ao entre dispositivos mais baratos (802.15.4) e redes 802.11 baseadas em TCP/IP (Transmission Control Protocol/Internet Protocol), abrindo algum espa co a cria c~ao de in umeras aplica c~oes, mais especi camente, aplica c~oes relacionadas com localiza c~ao, que representam, no fundo, o objectivo principal deste projecto. A cria c~ao das infraestruturas necess arias e do respectivo software de controlo, ainda que esta solu c~ao possa ser aplicada em muitos outros campos, foi direccionada especi camente para cumprir com alguns dos requisitos do sistema de localiza c~ao que venha eventualmente a ser criado. Assim, para al em dos Gateways, que fazem a tradu c~ao entre os dois standards j a mencionados, este projecto consiste na cria c~ao de Tags, pequenos dispositivos terminais de muito baixo custo e muito baixo consumo energ etico, que poder~ao ser acoplados aos objectos que necessitem de localiza c~ao. Estes dispositivos comunicam com os Gate- ways atrav es de uma liga c~ao wireless usando o standard IEEE 802.15.4 e, indirectamente, anunciam a sua localiza c~ao atrav es da disponibiliza c~ao do valor da for ca do sinal na conex~ao. Estas informa c~oes s~ao processadas e podem ser acedidas a partir de qualquer computador pessoal que esteja munido de um browser web e ligado a mesma rede.

Indoor positioning has become an important research field in recent years. This is due to the potential services or products that can be offered, which would be very useful for users in several applications, and the interesting commercialization possibilities. But nowadays the most developed positioning systems are used outdoors, and for example GNSSs do not provide indoor coverage, so the efforts are focused on other local radio technologies. In particular, ultra-wideband is the object of this thesis. In this thesis a set of cooperative algorithms are presented and intended for use in the localization phase of an ultra-wideband positioning system. Different approaches and points of view are shown in the literature related to the localization problem. Here there is a revision of the main concepts as well as some software implementations and their results in MATLAB, always trying to evaluate which is the best option in each situation. The Ultra-Wideband system considered in this thesis consists of a set of nodes, some of which have unknown positions that have to be estimated by the algorithms. These nodes have the ability of calculating distances between each other by measuring the round-triptime of ultra-wideband pulse signals. The distances are used as inputs to the algorithms to calculate the estimated positions of the nodes as outputs. The most remarkable detail is the cooperation, which means that the distances between any pair of nodes is used even when both have unknown positions, taking advantage of that information. The results show that using the cooperation, the algorithms can be very precise even in very demanding conditions when nodes can not communicate with the whole network due to a range limitation of the technology or physical obstacles. Therefore, cooperative algorithms represent a way to further investigate and improve the solutions for indoor positioning.

Dissertation (Ph.D.)--Worcester Polytechnic Institute.
Keywords: Time-of-arrival based ranging, indoor geolocation, cooperative localization, sensor networks, ultra wideband, measurement and modeling, cooperative localization algorithms. Includes bibliographical references (leaves 137-148).

This report evaluates various methods that can be used to position a smartphone running the Android platform, without the use of any special hardware or infrastructure and in conditions where GPS is unavailable or unreliable; such as indoors. Furthermore, it covers the implementation of such a system with the use of a deterministic fingerprinting method that is reasonably device independent, a method which involves measuring a series of reference points, called fingerprints, in an area and using those to locate the user. The project was carried on behalf of Sigma, a Swedish software consulting company.
Denna rapport evaluerar olika metoder för att bestämma positionen av en smartphone som använder sig av Android-plattformen. Metoden skall inte använda sig av någon speciell hårdvara eller infrastruktur samt kunna hantera förhållanden där GPS är otillgängligt eller opålitligt, som till exempel inomhus. Den beskriver också implementation av ett sådant system som använder sig av en deterministisk fingerprinting-metod som någorlunda väl kan hantera enheter av olika modeller, en metod som innebär att man mäter upp en mängd med referenspunkter, kallade fingerprints, och använder dessa för att placera användaren. Projektet utfördes på uppdrag av Sigma, ett svenskt mjukvarukonsultbolag.

The goal of the Internet of Things’ sensing technology is to provide LBS(location-based services); a key technology is finding out how to positioning the sensing devices. For positioning outdoors, mature tech-nology such as GPS and cellular network location can be used. There is little research about indoor positioning, and there is no finished product on the market. This paper shows how to use both Wi-Fi and ZigBee signal for position-ing; Wi-Fi to find the area position and ZigBee to find the coordinate position. The main contribution of this paper is described in the follow-ing: This paper will present an algorithm using kNN on a Wi-Fi signal, as a way to find the location area of users. The GPS signal cannot be used indoors, but there are usually numerous Wi-Fi signals, that can be used for indoor positioning. In this design, to build a dataset containing the number of locations and the Wi-Fi signal strength list of each location. When indoor positioning is needed, the KNN algorithm is used to compare the user’s Wi-Fi signal strength with the dataset and find the location number. When precise positioning is needed, the ZigBee signal should be used. In this paper two different methods for precise positioning in are used, one is an improved algorithm of triangle centroid algorithm where the positioning accuracy depends on the number of anchor points and the interval of each point. The other method is the neural network method. This method could give stable result with only four anchor points. Finally, there is a comparison of the methods mentioned in this paper : the Wi-Fi fingerprint method, the ZigBee triangle centroid algorithm, and neural network method.

Traffic from wireless and mobile devices is predicted to increase 10-fold between 2014 and 2019, surpassing wired data traffic by 2016. Given the expected radio frequency (RF) capacity crunch, this growing wireless demand will have to be met using a variety of new technologies exploiting other parts of the electromagnetic spectrum. Promising research areas include the Millimetre Band as well as Optical Wireless Communications (OWC). Millimetre Band demonstrations have accomplished ultrafast multi-Gigabit links, making use of state-of-the-art fibre transmission systems. However, complex opto-electronic (OE) interfaces are required to convert the optical carrier into Millimetre wireless signals. To avoid these interfaces, an all-optical transparent network is proposed here, spanning over both the fibre and OWC domains, in order to deliver ultrahigh data rates to mobile end-users in indoor environments. This is supported by the recent deployment of fibre-to-the-home (FTTH) networks creating the potential for Terabit aggregate connections at the user's doorstep. Therefore, infrared fibre-wireless-fibre (FWF) links are studied to support data rates over 100 Gb/s in nomadic applications. The link coverage is achieved via narrow beam beamsteering over a wide field-of-view (FOV) using suitable localization and tracking techniques. The proposed model is inherently bidirectional and transparent, i.e. independent of the data rate and modulation format. In this thesis, the potential for ultrafast wide coverage OWCs using SMF-based transceivers and coherent transmission is demonstrated. A record data rate of 418 Gb/s and 209 Gb/s with a wide FOV of θ_FOV=±30° and θ_FOV=±20°, respectively, is shown at a free space range of 3 m. To the best of our knowledge, this is the fastest demonstration of an indoor wireless link that offers practical room-scale coverage. The automated alignment of this FWF link is also demonstrated with the design and implementation a mm-accurate localization and tracking system. Finally, architectures for point-to-multipoint communications are explored in order to adapt the system to multiple users.

The work presented herein explores the ability of Ultra High Frequency Radio Frequency (UHF RF) devices, specifically (Radio Frequency Identification) RFID passive tags and Bluetooth Low Energy (BLE) to be used as tools to locate items of interest inside a building. Localization Systems based on these technologies are commercially available, but have failed to be widely adopted due to significant drawbacks in the accuracy and reliability of state of the art systems. It is the goal of this work to address that issue by identifying and potentially improving upon localization algorithms. The work presented here breaks the process of localization into distance estimations and trilateration algorithms to use those estimations to determine a 2D location. Distance estimations are the largest error source in trilateration. Several methods are proposed to improve speed and accuracy of measurements using additional information from frequency variations and phase angle information. Adding information from the characteristic signature of multipath signals allowed for a significant reduction in distance estimation error for both BLE and RFID which was quantified using neural network optimization techniques. The resulting error reduction algorithm was generalizable to completely new environments with very different multipath behavior and was a significant contribution of this work. Another significant contribution of this work is the experimental comparison of trilateration algorithms, which tested new and existing methods of trilateration for accuracy in a controlled environment using the same data sets. Several new or improved methods of triangulation are presented as well as traditional methods from the literature in the analysis. The Antenna Pattern Method represents a new way of compensating for the antenna radiation pattern and its potential impact on signal strength, which is also an important contribution of this effort. The performance of each algorithm for multiple types of inputs are compared and the resulting error matrix allows a potential system designer to select the best option given the particular system constraints.

To achieve the concrete aim of improving the positioning accuracy for large-scale indoor space in this thesis, we propose a weighted Gaussian and Mean hybrid filter (G-M filter) to obtain the G-M mean of received signal strength indicator (RSSI) measurements, which is implemented by taking the practically experimental measurements of received signal strength indicator and analyzing the characteristics of received signal strength indicator. Meanwhile, various path loss models have been utilized to estimate the separation between the transmitting antenna and the receiver (T-R separation) by calculating the G-M mean of received signal strength indicator, therefore, a dynamic-parameter path loss model has been proposed which can be appropriate to enhance the accuracy of estimated T-R separation and accurately describe the indoor position. Moreover, an improved fingerprint positioning has been proposed as the basic method combined with our tetrahedral trilateration scheme to reduce the positioning error of a large-scale 3D indoor space which can achieve the average localization error of 1.5 meters.

Thesis (M.S.) -- Worcester Polytechnic Institute.
Keywords: Performance Evaluation; RSS-based fingerprinting algorithm; Testbed; Indoor Geolocation; Indoor Positioning. Includes bibliographical references (p. 75-76).

Wireless positioning and tracking have long been a critical technology for various applications such as indoor/outdoor navigation, surveillance, tracking of assets and employees, and guided tours, among others. Proliferation of Internet of Things (IoT) devices, the evolution of smart cities, and vulnerabilities of traditional localization technologies to cyber-attacks such as jamming and spoofing of GPS necessitate development of novel radio frequency (RF) localization and tracking technologies that are accurate, energy-efficient, robust, scalable, non-invasive and secure. The main challenges that are considered in this research work are obtaining fundamental limits of localization accuracy using received signal strength (RSS) information with directional antennas, and use of burst and intermittent measurements for localization. In this dissertation, we consider various RSS-based techniques that rely on existing wireless infrastructures to obtain location information of corresponding IoT devices. In the first approach, we present a detailed study on localization accuracy of UHF RF IDentification (RFID) systems considering realistic radiation pattern of directional antennas. Radiation patterns of antennas and antenna arrays may significantly affect RSS in wireless networks. The sensitivity of tag antennas and receiver antennas play a crucial role. In this research, we obtain the fundamental limits of localization accuracy considering radiation patterns and sensitivity of the antennas by deriving Cramer-Rao Lower Bounds (CRLBs) using estimation theory techniques. In the second approach, we consider a millimeter Wave (mmWave) system with linear antenna array using beamforming radiation patterns to localize user equipment in an indoor environment. In the third approach, we introduce a tracking and occupancy monitoring system that uses ambient, bursty, and intermittent WiFi probe requests radiated from mobile devices. Burst and intermittent signals are prominent characteristics of IoT devices; using these features, we propose a tracking technique that uses interacting multiple models (IMM) with Kalman filtering. Finally, we tackle the problem of indoor UAV navigation to a wireless source using its Rayleigh fading RSS measurements. We propose a UAV navigation technique based on Q-learning that is a model-free reinforcement learning technique to tackle the variation in the RSS caused by Rayleigh fading.

Dissertation (Ph.D.)--Worcester Polytechnic Institute.
Keywords: Ray Tracing; Wideband Measurement; Dynamic Modeling of Ranging Error; ToA-Based Indoor Localization; NLoS Identification. Includes bibliographical references (leaves 147-159).

Indoor positioning systems have been widely studied in the last decade due to the need of humans for them especially in the large building such as malls, airports, hospitals...etc. Still, there is no suitable precise indoor positioning system which can be implemented for different indoor environments and situations. We should mention military urban and emergency situations. In military urban and emergency response operations, the time is a crucial issue, and a precise positioning system with a clear indoor covering is a highly prerequisite tool to enhance safety. It should be seamless, low, frugal, power efficacious, low cost and supply less meter-level accuracy. In emergency scenarios, we don't have enough flexibility and time to install all anchor nodes in a proper situation that may help to obtain an appropriate accuracy for locating a mobile station, but command centers require observing their operational forces, and rescuers demand to detect potential victims to perform proper care. The most common users for these situations are the firefighters, police, military, and civilians. The main goal of this Ph.D. dissertation is to create an accurate indoor positioning (IP) system that could be used in different indoor environments and situation, especially for the emergency situation. So, we create this system through different steps as explained below. First, we have considered the study of different radio technologies to choose the suitable radio technology called Ultra wide band (UWB) radio technology. The reasons of selection the UWB and the commercial device that implements such technology are explained in details in chapters 3 and 4. Afterward, due to some impacts of the UWB in indoor environments (see chapters 4 and 5), we continue the study of NLOS identification and mitigation methods. In these chapters, we create two different NLOS identification and mitigation methods using a commercial UWB device experimentally. The first method used two parameters extracted from the UWB device to identify the propagation channel and map information of the building that the method is experimentally done in it to mitigate the NLOS channel. The second method of NLOS identification and mitigation used three parameters extracting from the UWB device to be an input set of the Fuzzy logic technique used to identify the propagation channels. In this identification method, it is not only to identify the prorogation channel to NLOS and LOS but also to divide the NLOS channel into hard and soft channels. Then, we created a database that includes the three parameters and the distance Bias to mitigate the NLOS channel for obtaining an accurately estimated distance to be used for creating an accurate IP system. Finally, with the aim of applying our designs to mass market applications, we move to create a novel IP system using the UWB technology called anchor selection (AS). In this technique, we focus on using fewer sensors (anchor nodes) to locate a mobile station under harsh circumstances such as scenarios where the installation area of the anchor nodes is narrow and/or the installation time should be very short. The proposed approach is based on grouping anchor nodes in different sets and evaluating the positioning error of each of these groups by means of a novel mean squared error (MSE)-based methodology. A virtual node approach is also proposed to consider the case where position must be computed with only two anchor nodes.

Received Signal Strength Indication (RSSI) fingerprinting is a popular technique in the fieldof indoor positioning. Many studies on the subject exist acknowledging Wi-Fi signal variationconnected to Wi-Fi signals, but does not discuss possible signal variation created byconnected devices nor consequential precision loss.Understanding more about the origins of signal variation in received signal strength indication(RSSI) fingerprinting would help deal with or prevent them as well as provide moreknowledge for applications based on such signals. Environments with a varying number ofconnected devices would benefit from knowing changes in localization precision resultingfrom the devices connecting and disconnecting from the access point because it wouldindicate whether workarounds for such circumstances would be necessary.To address this issue, the work presented here focuses on how the precision of RSSIfingerprinting vary given different levels of connected Wi-Fi devices. It was carried out byconducting real world experiments at times of low- and normal levels of connected devices toaccess points on two separate locations and evaluating precision changes between statedactivity levels. These experiments took place at the University of Borås as well as at Ericssonin Borås.Experimental findings indicate that the accuracy does deteriorate in higher levels of activitythan in low activity, even though not enough evidence to determine the precision ofdeterioration. The experiments thereby provide a foundation for location-based applicationsand services that can communicate the level of positional error that exist in differentenvironments which would make the users aware but also make the applications adaptaccordingly to different environments. Based on the precision achieved, we identify variousapplications that would benefit from our proposed model. These were applications that wouldtrack mobile resources, find immobile resources, find the movement flows of users as well asnavigation- and Wi-Fi coverage applications.Further research for investigating the exact correlation between access point stress andprecision loss is proposed to fully understand the implications connected devices have onRSSI fingerprinting.

Master Thesis presents the system consisting of software and components of Arduinoplatform along with modules compatible with it, intended for use indoor. The device fulfils thefollowing requirements which are: to ensure privacy preservation, low energy consumptionand the wireless nature. This thesis reports the development of a prototype that would ensure step detection,posture detection, indoor localization, tumble detection and heart rate detection using themicrocontroller, AltIMU-10 v4 module, heart rate monitor, WiFi module and battery. Veryimportant part of the thesis is algorithm, which uses comparison function. Thanks to thewireless nature of a prototype, the system collects data regardless of an environment and sendthem directly to every device supported by Microsoft Windows platform, Linux platform orOS X platform, which are monitored by the supervisor, who takes care of the solitary person. The main contributions of the prototype are: indoor localization, identification andclassification of occurring situations and monitoring vital signs of the solitary person. To ensure indoor localization the prototype must collect data from accelerometer. Ofcourse data from AltIMU-10 v4 module in basic form are useless for the supervisor, so thealgorithm, using by the prototype, is programmed to processing and filtering it. Algorithm is also used to identification and classification occurring situations. Datafrom accelerometer are processed by it and compared with the created pattern. Monitoring vital signs of the solitary person are more complicated function, because itrequires not only data from accelerometer, but also from heart rate monitor. This sensor isusing to the analyzing condition of the patient when dangerous situation occurs.

Indoor localisation technologies are a core component of Smart Homes. Many applications within Smart Homes benefit from localisation technologies to determine the locations of things, objects and people. The tremendous characteristics of the Radio Frequency Identification (RFID) systems have become one of the enabler technologies in the Internet of Things (IOT) that connect objects and things wirelessly. RFID is a promising technology in indoor positioning that not only uniquely identifies entities but also locates affixed RFID tags on objects or subjects in stationary and real-time. The rapid advancement in RFID-based systems has sparked the interest of researchers in Smart Homes to employ RFID technologies and potentials to assist with optimising (non-) pervasive healthcare systems in automated homes. In this research localisation techniques and enabled positioning sensors are investigated. Passive RFID sensors are used to localise passive tags that are affixed to Smart Home objects and track the movement of individuals in stationary and real-time settings. In this study, we develop an affordable passive localisation platform using inexpensive passive RFID sensors. To fillful this aim, a passive localisation framework using minimum tracking resources (RFID sensors) has been designed. A localisation prototype and localisation application that examined the affixed RFID tag on objects to evaluate our proposed locaisation framework was then developed. Localising algorithms were utilised to achieve enhanced accuracy of localising one particular passive tag which that affixed to target objects. This thesis uses a general enough approach so that it could be applied more widely to other applications in addition to Health Smart Homes. A passive RFID localising framework is designed and developed through systematic procedures. A localising platform is built to test the proposed framework, along with developing a RFID tracking application using Java programming language and further data analysis in MATLAB. This project applies localisation procedures and evaluates them experimentally. The experimental study positively confirms that our proposed localisation framework is capable of enhancing the accuracy of the location of the tracked individual. The low-cost design uses only one passive RFID target tag, one RFID reader and three to four antennas.

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
Smart Campus has emerged as a study platform of a Smart City. There are some similarities between the Campus and a City. Due to this, is possible use a Smart Campus as attesting bench and then apply these investigations to implement in a Smart City. One of this potential technologies is the Indoor Positioning System using the Wi-Fi network. The aim of this work is research and implement a mobile application to carry out the indoor positioning in the context of the UJI Smart Campus. The prototype developed allows to perform the first part of the Wi-Fi Indoor Positioning, the mapping phase. This application implements a system to display and all UJI cartography (campus basemap, UJI buildings and UJI buildings interiors). When whole system will be developed, it will allow implement the indoor positioning in a future applications for the Smart Campus.

Wayfinding and navigation are essential aspects of independent living that heavily rely on the sense of vision. Walking in a complex building requires knowing exact location to find a suitable path to the desired destination, avoiding obstacles and monitoring orientation and movement along the route. People who do not have access to sight-dependent information, such as that provided by signage, maps and environmental cues, can encounter challenges in achieving these tasks independently. They can rely on assistance from others or maintain their independence by using assistive technologies and the resources provided by smart environments. Several solutions have adapted technological innovations to combat navigation in an indoor environment over the last few years. However, there remains a significant lack of a complete solution to aid the navigation requirements of visually impaired (VI) people. The use of a single technology cannot provide a solution to fulfil all the navigation difficulties faced. A hybrid solution using Internet of Things (IoT) devices and deep learning techniques to discern the patterns of an indoor environment may help VI people gain confidence to travel independently. This thesis aims to improve the independence and enhance the journey of VI people in an indoor setting with the proposed framework, using a smartphone. The thesis proposes a novel framework, Indoor-Nav, to provide a VI-friendly path to avoid obstacles and predict the user s position. The components include Ortho-PATH, Blue Dot for VI People (BVIP), and a deep learning-based indoor positioning model. The work establishes a novel collision-free pathfinding algorithm, Orth-PATH, to generate a VI-friendly path via sensing a grid-based indoor space. Further, to ensure correct movement, with the use of beacons and a smartphone, BVIP monitors the movements and relative position of the moving user. In dark areas without external devices, the research tests the feasibility of using sensory information from a smartphone with a pre-trained regression-based deep learning model to predict the user s absolute position. The work accomplishes a diverse range of simulations and experiments to confirm the performance and effectiveness of the proposed framework and its components. The results show that Indoor-Nav is the first type of pathfinding algorithm to provide a novel path to reflect the needs of VI people. The approach designs a path alongside walls, avoiding obstacles, and this research benchmarks the approach with other popular pathfinding algorithms. Further, this research develops a smartphone-based application to test the trajectories of a moving user in an indoor environment.

Smart homes for aged care allow residents to stay in their own homes longer without having to move to assisted living facilities such as nursing homes. The aim of smart homes for aged care is to provide ambient assisted living using technologies that provide systems of monitoring of medical conditions, monitoring of activities of daily living, provide alerts, warnings, and reminders. Sensors of various forms and wearables are necessary to achieve the functionality of a smart home for aged care. It is also well known that decision systems that combine decisions of multiple sensor technologies improve the accuracy of decisions. The location identification is one of the key decision-making systems that can be combined with other sensor platforms for improving accuracy. This thesis looks at location identification systems based on RFID technology. RFID systems typically use received signal strength and trilateration techniques to determine the location of an object. The accuracy of location of such systems is not precise and may vary depending on the measurement location. The goal of this work is to examine if phase angle information can be combined with received signal strength data to improve location identification in RFID-based systems.

碩士
中華大學
電機工程學系(所)
98
With the every-changing technology, positioning systems are now widely used in biological information, emergency rescue, public facilities and personal use, not just in the military aspect. There are various ways to know the location of the user. It commonly used the global positioning system to know about the user’s location in the outdoor space. However, the global positioning system in the indoor environment indoor is vulnerable to interference, etc. It results that global positioning system can not be effectively used in the indoor environment. Therefore, in recent years, many researchers have used the techniques of wireless sensor networks to implement for indoor wireless positioning system. This type of indoor positioning systems can make use of received signal strength or the link quality indication measurement to achieve location-based services. This paper first use the mean of the link quality indication to reduce the receiver link quality indication of the noise interference, then following by radial basis function network trained to identify the location of user. The Zigbee wireless sensor modules is implemented in the system. Experimental results show that the use of multiple radial basis function network accuracy is better than other methods available to the average error of 1.47 meters. This study can be applied to random distribution of wireless sensor networks, the future will provide a wide range of location-based services.

碩士
國立臺灣大學
資訊管理學研究所
92
Recently, the service of indoor positioning system has gradually become a hot issue; and with the maturation of IEEE 802.11 wireless technology, it has been the first choice for indoor positioning system. Owing to the sensitivity of RF signal of 802.11 which may attenuated by obstacles and human body, traditional outdoor positioning algorithm, such as triangle positioning algorithm, is not suitable to use for indoor positioning. In order to accurately position in indoor space, many researches have pointed out that a previously built RSSI (Received Signal Strength Indicator) database is necessary. By comparing the RSS vector received at mobile nodes with RSSI database, we can precisely position the location of mobile users. However, collecting RSS for all grids of indoor space costs lots of human resource. Hence, the purpose of this thesis is to propose a method, which selects measure points elaborately, and collocates with a nice RSS inference algorithm, and then we can build up well RSSI database with relatively lower cost. In this research we proposed a method that selects suitable quantity of measure points at elaborately selected locations, and infers the signal strength of the other points based on these selected measure points to reduce signal strength collecting cost.

The Global Positioning System (GPS) is the most popular positioning system among some operational Global Navigation Satellite Systems (GNSS). However, GNSS suffer from accuracy deterioration and interruption of services in dense urban areas and are almost unavailable indoors. Although high-sensitivity receivers improve signal acquisition indoors, multipath is still be a challenging problem that affects accuracy especially indoors where a direct line of sight between transmitter and receiver almost never exist. Moreover, the wireless signal features are significantly jeopardized by obstacles and constructions indoors. To address these challenges, this research came in the context of proposing an alternative positioning system that is designed for GPS-denied environment and especially for indoors. Cramer-Rao Lower-Bound (CRLB) analysis was used to estimate the lower bound accuracy of different positioning methods indoors. Based on CRLB analysis, this research approached the wireless positioning problem indoors utilizing received signal strength (RSS) to achieve the following: 1) Developing new estimation methods to model the wireless RSS patterns in indoors. 2) Designing adaptive RSS-based wireless positioning methods for indoors. 3) Establishing a consistent framework for indoor wireless positioning systems. 4) Developing new methods to integrate inertial/odometer-based navigation systems with the developed wireless positioning methods for further improvements. The theoretical basis of the work was built on nonlinear stochastic estimation techniques including Particle Filtering, Gaussian Process Regression, Fast Orthogonal Search, Least-Squares, and Radial Basis Functions Neural Networks. All the proposed wireless positioning methods were developed and physically realized on Android-based smart-phones using the IEEE 802.11 WLANs (WiFi). In addition, successful integration with inertial/odometer sensors of mobile robots has been performed on embedded systems. Both theoretical analysis and experimental results showed significant improvements in modeling RSS indoors dynamically without offline training achieving a positioning accuracy of 1-3 meters. Sub-meter accuracy was achieved via integration with inertial/odometer sensors.
Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2013-03-25 16:11:59.518

University of Technology, Sydney. Faculty of Engineering and Information Technology.
This thesis investigates High Frequency Radio Frequency Identification (HF RFID) based positioning using a novel concept of multi-loop bridge reader antenna to localise moving objects such as autonomous wheelchairs in indoor environments. Typical HF RFIDs operate at 13.56 MHz and employ passive tags which are excited by the magnetic field radiated by the reader antenna. Positioning of moving objects using HF RFID systems derive location information by averaging the coordinates of detected passive floor tags by a portable reader antenna which are then recorded in the reader’s memory and database. To successfully detect floor tags, the reader’s antenna usually installed at the base of a moving object needs to be parallel to the floor. The magnetic field radiated by the HF RFID antenna is confined within its near field zone i.e., it is confined to a very close proximity of the antenna. This property of HF RFID helps to minimise interference to other appliances that may be present within the localisation area. Thus, HF RFID based positioning offers great potential benefit in providing location assistance in environments such as nursing homes, health care facilities, hospitals etc. However, despite the significant developments that have occurred in this field, there still exist problems with positioning accuracies obtainable mainly due to the uncertainty of the reader recognition area (RRA) of the reader antenna, which has not been fully addressed in literature. This thesis aims to address this problem by proposing the concept of multi-loop bridge reader antenna so that the reader recognition area is divided into multiple sub zones and an error signal (bridge signal) in terms of the position of the tag will be generated that helps to reduce the position uncertainty. The thesis starts with an investigation of the methods for creating multiple zones of RRA and the concept of bridge loop antenna from point of view of near magnetic fields. Different types of loop antennas for employing at the reader are electromagnetically analysed using both closed form solutions and numerical computations. The formation of reader recognition area (RRA) from different arrangements of loop reader antennas is also studied. To ensure that proposed bridge antennas can perform in realistic, non-ideal indoor environments where they are affected by proximity of metallic objects etc, we proposed methods of improvement. Equivalent circuits that reduce the computational complexity but can provide a broader understanding of the behaviour of bridge antennas have been formulated. This has lead to investigation of methods to minimise and/or eliminate the effect of metallic objects on the bridge signals. Next, we investigate the applicability of the proposed bridge loop antenna for the localisation and positioning of an autonomous wheel chair resulting in a realistic implementation of HF RFID based positioning system. The system is then tested to localise an autonomous wheelchair in an indoor environment using a grid of passive floor tags. Novel algorithms are proposed to estimate the position and orientation of the moving object using bridge signals generated by the bridge antenna coupled with the available dynamic information of the wheelchair. A comparison of our experimental results with the published results in the literature revealed significant improvements achieved by our proposed methods over existing techniques for estimating both, the orientation and position. Further, we demonstrate that the proposed technique obtains accurate position and estimation using much lesser number of floor tags (increased sparcity) than any of the currently published method, thus, contributing to simplified and easily expandable tag infrastructure deployment. We further extend the use of bridge loop antenna for situation when multiple tags are detected using the method of load modulation of the tags. When multiple tags present within the RRA of the bridge loop antenna, the resulting bridge signals incorporate information from all of the detected tags thus making it difficult to locate individual tags. To overcome this, we utilise states of the tag’s load modulation to separate these bridge signals, which then allow us to utilise them to estimate instantaneous position and orientation of the moving object. We performed analysis using equivalent circuits, as well as computational electromagnetic modelling of realistic antennas, which are then compared with experimental measurements carried on prototype systems. The comparison showed good agreement which validate our proposed method. Thus, the thesis incorporate contributions on various aspects of bridge loop reader antenna for HF RFID based positioning system. All full wave electromagnetic computations and simulations were carried by using a well known antenna design package “FEKO”. All the key analyses, equivalent circuits, antenna models and computational results for the proposed antennas and algorithms have been verified using extensive experimental campaigns to demonstrate the practical usefulness of the proposed methods. It is hoped that the findings in this thesis will result in newer efficient positioning systems in future.

Indoor positioning is an enabling technology primed to impact the indoor application space as Global Navigation Satellite Systems (GNSS) did for the outdoor space. Amongst the competing positioning technologies are methods of different mediums: light, radio frequency and ultra-wideband, ultrasonic, and imaging; methods of different modalities: received signal strength, angle-of-arrival, time-of-flight; and methods of different mathematics: trilateration, triangulation, machine learning, and signal processing. Light-based positioning compared to other positioning schemes exploits fixed-location directional luminaires placed regularly throughout a space as anchor points -- there is an efficiency argument for multi-purpose lighting and a cost-share argument for infrastructure-based positioning. Similar to the satellite infrastructure with GNSS, with anchor points and models for light propagation and construction, position is estimated based on received signals at active photodiode-equipped target devices. Received signal strength, a common first order attribute, alone is not noise resilient enough for centimeter-level 3D positioning. Methods using angle diversity produce better results particularly in 3D but with more complex hardware. For this dissertation, we exploit angle diversity and modulated optical sources in light-based positioning systems to estimate position to centimeter-level accuracy in 3D. We propose, analyze, and contribute two novel positioning schemes that use these concepts. One of the proposed schemes is a new hybrid 3D indoor positioning technique, Ray-Surface Positioning (RSP), which incorporates a narrow field-of-view (FOV) optical source (Ray) with wide diffuse optical sources (Surfaces) to position active devices in 3D. The second scheme, a Zone-based Positioning Service (ZPS), is a positioning scheme and architecture that incorporates an angle diverse narrow FOV optical source at the positioned device. This unique design decision allows the active device to position itself directly with respect to photovoltaic anchor points but also to position other devices in its FOV called transitive positioning. Along with these contributions, we also investigate several other related topics. Concisely, as part of the dissertation, we contribute (a) review of the state-of-the-art, (b) analysis for steering Lambertian sources, (c) method of creating angle diversity from a narrow FOV optical source, (d) novel positioning approaches in (1) RSP and (2) ZPS, (e) proof of concept prototypes for (1) RSP and (2) ZPS, and (f) architectures for indoor positioning applications.

博士
國立中正大學
電機工程研究所
99
In this dissertation work, two wireless indoor positioning systems aiming for decimeter positioning accuracy, low circuit complexity, and multipath suppression, were investigated and developed. In both systems, only the received signal strength (RSS) information is required for the target’s direction-of-arrival (DOA) estimation so that the system complexity as well as infrastructure cost can be significantly reduced. However, large positioning error could occur due to the multi-path fading effect on the received signal strength. Therefore, the indoor multipath channel modeling for linear and planar array was also derived mathematically. To eliminate the multipath signals, two positioning technologies were proposed, including the non-orthogonal beamforming and the selection-and-average error correct algorithm. The first wireless indoor positioning system based on the non-orthogonal beam linear arrays was implemented by incorporating two linear array receivers to determine the position of target. The circular-polarized antenna array with high directivity was chosen to suppress the multipath interference. In addition, the beam orthogonality was demoted on purpose so that the angular position can be estimated based on the power ratio of two adjacent beams. The second wireless indoor positioning system was implemented by using a 2×2 planar array with the selection-and-average error correction algorithm. The multiple power ratio detection curves were generated due to the beam steering, while the selection-and-average error correction algorithm was proposed to improve the location accuracy. The proposed 2-D precise DOA estimation can be achieved by 1-D pattern calibrations in two axils only. Additionally, numerous tunable phase shifter MMICs, which are the essential component in phased array system, were designed and implemented aiming for low loss-variation performance over quadrants of phase-shift range. The inductively over-coupled quadrature hybrids were theoretically analyzed, such that the phase, amplitude imbalance, and circuit size can be significantly reduced. During the course of this work, four phase shifters MMICs designed at 2.45, 24, and 60 GHz were implemented in 0.18-um CMOS technology.

博士
國立中正大學
電機工程研究所
100
In this dissertation work, two novel 2-D and 3-D indoor positioning systems using one single base station node were investigated and developed. To overcome severe indoor multipath interference, switched injection-locked active tag and circular polarization antenna array are utilized herein. More advantages come along including low material and infrastructure cost, unnecessary time-consuming calibration, and precise positioning accuracy. Firstly, combined with frequency-modulated continuous wave (FMCW) and switched-beam phased antenna array, the 2-D indoor positioning system can provide both distance (lateration) and angular (angulation) information of unknown target using newly proposed polar positioning method. Employing the switched injection-locked technique can successfully distinguish the desired modulated signal from the un-modulated echoes caused by steady obstacles. Meanwhile, the angular resolution can be upgraded by comparing the received adjacent pattern power ratio (APPR) by a 1×4 switched-beam antenna array receiver. Secondly, the joint FMCW radar and dynamic Σ-Δ radar are proposed and implemented to further locate the target with three-dimensional information in one single positioning node. Based on a 2×2 circular-polarized antenna array, the FMCW-based transceiver provides the lateration information, while the dynamic Σ-Δ radar gives latitude and longitude angular information. Combining the error detection curves under sectorizing algorithm, the locating FOV can successfully be extended from 40° to 60°. Finally, two approaches to enhance Butler matrix’s beam resolutions without gaining the circuit size are proposed and designed for further improvement in the angular estimation accuracy. An enhanced switching/steering stripline-based Butler matrix combining both techniques is proposed, where the radiation beam is initially switched to a certain direction through the Butler matrix, and then slightly adjusted by the tunable phase shifters. In addition, the twin-feeding Butler matrix is also designed using grounded coplanar-waveguide to increase beam number from N to (2N-1). The space resolution can be further improved by varying the power ratio of those two feeding signals.

Philosophy Doctorate Thesis Electronic and Computers Engineering
The availability of a reliable and accurate indoor positioning system (IPS) for emergency responders during on-duty missions is regarded as an essential tool to improve situational awareness of both the emergency responders and the incident commander. This tool would facilitate the mission planning, coordination and accomplishment, as well as, decrease the number of on-duty deaths. Due to the absence of global positioning system (GPS) signal in indoor environments, many other signals and sensors have been proposed for indoor usage. However, the challenging scenarios faced by emergency responders imply explicit restrictions and requirements on the design of an IPS, making the use of some technologies, techniques, and methods inadequate on these scenarios. Alongside with the position information, monitoring physiological and environmental parameters is also vital to improve the emergency responders’ safety. So, to monitor all these parameters, a cyber -physical system (CPS), designated by PROTACTICAL CPS, is proposed. This system aims to improve the decision making at several emergency responders’ operation stages (e.g., emergency responder, teams, and incident commander), and is capable of detecting, in real-time, life-threatening scenarios. Different sensor nodes, called node-PROTACTICAL, are integrated into a personal protective equipment (PPE) to acquire the desired parameters. Two wireless networks are used to send the acquired information to the incident commander, a wireless body sensor network (WBSN) and an Ad-Hoc network. The former relies on the ZigBee technology and is responsible for managing the communication with the nodes-PROTACTICAL. On the other hand, the Ad-Hoc network relies on Wi-Fi technology and is responsible for the communication between the PPE and the incident commander. For the estimation of the emergency responder’s position, a hybrid IPS integrated into the PROTACTICAL CPS is proposed. This IPS is based on an indirect remote positioning topology and is composed of three modules (radio signal-based, IMU-based, and data fusion). The present work focuses essentially on the design and evaluation of an IPS for emergency responders. This involves the definition of the specific requirements, selection of technologies, evaluation of positioning methods and their combination to overcome the limitations imposed by the emergency responders’ scenarios. For the radio signal-based module, the ultra-wideband (UWB) technology was selected because of its immunity to noise and high accuracy of the ranging measurements. A measurement campaign was carried out to assess the performance of the ranging measurements under different propagation conditions and, the worst scenario occurs when the signal is blocked by the human body. So, non-line-ofsight (NLOS) identification and error mitigation algorithms are proposed to reduce the ranging measurement error under NLOS conditions. Then, four positioning algorithms are compared and evaluated under different conditions (e.g., environments with different propagation conditions, static and dynamic target, and with or without NLOS influence due to the human body). The previous study confirmed some weaknesses that can be compensated by another positioning method and thus a pedestrian dead reckoning (PDR) system based on foot-mounted inertial sensors is proposed and evaluated. This system is capable of, simultaneously, estimating the distance travelled and the emergency responder’s attitude. An extended Kalman filter (EKF) aided by zero velocity updates (ZUPT) is implemented to refine the emergency responder’s position and heading. Finally, a data fusion algorithm based on a Kalman filter is proposed to combine the UWB and PDR estimates. The data fusion algorithm is assisted by a decision-making algorithm that rejects the UWB position estimation when two or more ranging measurements are in NLOS. The performance of the data fusion method is assessed with three UWB positioning algorithms.
A existência de um sistema de localização indoor (IPS) confiável e preciso que possa ser utilizado por equipas de emergência durante as suas missões é considerado uma ferramenta essencial para melhorar a perceção da situação pelas equipas de emergência e pelo comando. Esta ferramenta facilitaria o planeamento, coordenação e realização da missão, além de diminuir o número de acidentes graves e mesmo fatais. Devido à ausência de sinal do sistema de posicionamento global (GPS) em muitas situações, muitas outras tecnologias e sensores foram propostos para uso em edifícios e ambientes sem cobertura GPS. No entanto, os cenários enfrentados pelas equipas de emergência impõem restrições e requisitos específicos sobre a conceção do IPS, tornando o uso de algumas tecnologias, técnicas e métodos inadequados nesses casos. Juntamente com a informação da posição, a monitorização de parâmetros fisiológicos e ambientais também é importante para melhorar a segurança das equipas de emergência. Assim, para monitorizar todos esses parâmetros, é proposto um cyber-physical system (CPS), designado por PROTACTICAL CPS. Este sistema visa melhorar a tomada de decisões nos vários estágios da missão (por exemplo, ao nível do bombeiro, das equipas e do comando) e é capaz de detetar, em tempo real, cenários que ameaçam a vida das equipas de emergência. Diferentes nós sensores, chamados nó-PROTACTICAL, são integrados em um equipamento de proteção pessoal (EPI) para a aquisição dos parâmetros desejados. A informação adquirida é enviada ao comandante através de duas redes sem fios, uma wireless body sensor network (WBSN) e uma rede Ad-Hoc. A primeira baseia-se na tecnologia ZigBee e é responsável por assegurar a comunicação com os nós-PROTACTICAL. Por outro lado, a rede Ad-Hoc depende da tecnologia Wi-Fi e é responsável pela comunicação entre o EPI e o comando. Para a localização indoor, é proposto um IPS híbrido integrado no PROTACTICAL CPS. Este IPS é baseado na topologia de posicionamento remoto indireto e é composto por três módulos (baseado em sinal de rádio, baseado em IMU e fusão de dados). O presente trabalho incide no design e avaliação de um IPS para equipas de emergência. Isso envolve a definição dos requisitos específicos, seleção das tecnologias, avaliação dos algoritmos de localização e a sua combinação de modo a superar as limitações impostas pelos cenários das equipas de emergência. Para o módulo baseado em sinal de rádio, a tecnologia ultra-wideband (UWB) foi selecionada devido à sua imunidade ao ruído e precisão das medições de distância. Foi realizado um conjunto de testes para avaliar o desempenho destas medições em diferentes condições de propagação, verificando-se que o pior cenário ocorre quando o sinal é bloqueado pelo corpo humano. Para ultrapassar esta dificuldade, é proposto um algoritmo para a identificação das medições de distância obtidas sem linha de visão (NLOS) e assim mitigar o erro das respetivas medições. De seguida, quatro algoritmos de posicionamento são comparados e avaliados sob diferentes condições (p.e., ambientes com diferentes condições de propagação, alvo estático e dinâmico e com ou sem influência do NLOS devido ao corpo humano). O estudo anterior confirmou algumas fragilidades que podem ser compensadas por outro método de localização e, desse modo, é proposto e avaliado um sistema de pedestrian dead reckoning (PDR) baseado em sensores inerciais montados no pé. Este sistema é capaz de estimar a distância percorrida e a direção do movimento. Um filtro Kalman estendido (EKF) auxiliado por atualizações de velocidade zero (ZUPT) é implementado para refinar a posição e a direção do movimento do utilizador. Finalmente, propõe-se um algoritmo de fusão de dados baseado no filtro de Kalman para combinar as estimativas de posição provenientes dos subsistemas UWB e PDR. O algoritmo de fusão de dados é assistido por um algoritmo de decisão que rejeita a estimativa da posição UWB quando duas ou mais medidas de variação estão em NLOS. O desempenho do método de fusão de dados é avaliado com três algoritmos de posicionamento UWB.
Fundação para a Ciência e a Tecnologia (FCT), for the financial support under the PhD scholarship SFRH/BD/91477/2012. I would also like to acknowledge the doctoral program in Electronics and Computer Engineering for supporting this work.

Indiana University-Purdue University Indianapolis (IUPUI)
With the advances in embedded technology and the omnipresence of smartphones, tracking systems do not need to be confined to a specific tracking environment. By introducing mobile devices into a tracking system, we can leverage their mobility and the availability of multiple sensors such as camera, Wi-Fi, Bluetooth and Inertial sensors. This thesis proposes to improve the existing tracking systems, enhanced Distributed Tracking System (e-DTS 2.0) [19] and enhanced Distributed Object Tracking System (eDOTS)[26], in the form of e-DTS 3.0 and provides an empirical analysis of these improvements. The enhancements proposed are to introduce Android-based mobile devices into the tracking system, to use multiple sensors on the mobile devices such as the camera, the Wi-Fi and Bluetooth sensors and inertial sensors and to utilize possible resources that may be available in the environment to make the tracking opportunistic. This thesis empirically validates the proposed enhancements through the experiments carried out on a prototype of e-DTS 3.0.